Biology subjects

Gupta, A. M.

Publications and source records attributed to Gupta, A. M..

2 recordsLinked to original sources

bioRxiv2024

Structural Adaptations of HepI Enzymes in Proteobacteria: Insights into Evolutionary Resilience and Functional Dynamics

Since lipopolysaccharide molecules are highly variable in their structure while also being essential for bacterial cell survival, we hypothesized that enzymes involved in its biosynthesis may exhibit differences that could be used to predict the likelihood of survival in different ecological niches. We examined the sequence variability of orthologues of Heptosyltransferase I (HepI), which is found in all lipopolysaccharide (LPS) containing Gram-negative bacteria. We identified two different sequence motifs within the N-terminal domain of HepI, which correlated with differences in the Lipid A portion of the LPS. Further, we compared the protein structure of HepI from Escherichia coli with a structural model we generated that incorporated the alternate sequence motif. Molecular dynamics simulations of these two proteins, recapitulated our findings, that proteins with the E. coli-like sequence motif maintained a larger enzyme active site, while the mutated structural model undergoes rearrangements that lead to a smaller N-terminal active site pocket. This work revealed sequence-structure-function relationships that can be used to determine if a species incorporates a Heptose residue onto Lipid A chains containing one or two 3-deoxy-D-manno-oct-2-ulosonic acid (Kdo) residues. Since research suggests that the number of Kdo residues in LPS impacts the overall immune response to the LPS endotoxin, this work could aid in our understanding of the pathogenic effects of human-bacterial interactions. Understanding the sequence-structural adaptations of HepI enzymes across proteobacteria sheds light on their evolutionary resilience and functional versatility. HighlightsO_LILipopolysaccharide (LPS) structure varies between organisms C_LIO_LIHeptosytransferase I sequence motifs allow prediction of LPS structural features C_LIO_LIAdaptations of HepI enzymes reveal evolutionary resilience and functional versatility C_LI

evolutionary biology↗

bioRxiv2017

Distribution of Sigma factors delineates segregation of virulent and avirulent Mycobacterium

Sigma factors, in combination with RNA polymerase and several transcription factors play specific role in expression of housekeeping as well as various stress responsive genes in mycobacterial species. The genus Mycobacterium includes a wide range of species under major pathogens, opportunists and non-pathogens. The number and combination of sigma factors is extremely diversified among Mycobacterium. We have performed comparative genome analysis among 40 different species of Mycobacterium whose whole genome sequence is available, in order to identify the distribution of sigma factors. The study illustrate that SigC, SigD, SigG, SigH, SigK and SigI are dominant among the true pathogens. Moreover, 16S rDNA based phylogenetic analyses distinctly differentiate the slow growing Mycobacterium from the fast growers, and clusters the true pathogens from the opportunists and non-pathogens. While evaluating the similarity coefficient upon the allotment of sigma factors of different Mycobacterium species through UPGMA dendrogram analysis, it is apparent that the true pathogens are grouped separately following the similar trend observed from evolutionary approach. Sigma factors playing dominant role in pathogenicity are found stable in nature with high aliphatic index thereby remain flexible at a wide range of temperature. The comparative distribution of six well known virulence factors of Mycobacterium - PhoP, PcaA, FbpA, Mce1B, KatG and PE_PGRS and various sigma factors justify the allotment pattern of mycobacterial sigma factors among pathogenic species. The pathogenicity responsible sigma factors elicit close resemblance with few notable characters of the known virulence factors. Thus the analysis renders that the distribution of sigma factors of different species of Mycobacterium can be a potential tool to predict the pathogenicity index of this genus.

microbiology↗